Skill audit report
An open-source Python framework for hybrid quantum-classical machine learning.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
PASS86
2.2K GitHub stars
Stars/forks activity
PASS83
2.2K stars, 653 forks; issue activity unavailable in current metadata
Recent maintenance
INFO76
4mo since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
INFO74
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
PASS82
network or browser surface
Install availability
PASS92
npx skills add tensorflow/quantum
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO72
filesystem or document access, network or browser access
Repository evidence
PASS86
https://github.com/tensorflow/quantum
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add tensorflow/quantum
Repository
88
https://github.com/tensorflow/quantum
License
86
Apache-2.0
Maintenance
76
4mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
84
Usable description available
Dependency risk
82
network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
72
filesystem or document access, network or browser access
Stars/forks activity
83
2.2K stars, 653 forks; issue activity unavailable in current metadata
Adoption
88
2.2K GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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